Evaluation of the Intel Xeon Phi and NVIDIA K80 as accelerators for two-dimensional panel codes
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To predict the properties of fluid flow over a solid geometry is an important engineering problem. In many applications so-called panel methods (or boundary element methods) have become the standard approach to solve the corresponding partial differential equation. Since panel methods in two dimensions are computationally cheap, they are well suited as the inner solver in an optimization algorithm. In this paper we evaluate the performance of the Intel Xeon Phi 7120 and the NVIDIA K80 to accelerate such an optimization algorithm. For that purpose, we have implemented an optimized version of the algorithm on the CPU and Xeon Phi (based on OpenMP, vectorization, and the Intel MKL library) and on the GPU (based on CUDA and the MAGMA library). We present timing results for all codes and discuss the similarities and differences between the three implementations. Overall, we observe a speedup of approximately 2.5 for adding a Intel Xeon Phi 7120 to a dual socket workstation and a speedup between 3 and 3.5 for adding a NVIDIA K80 to a dual socket workstation.
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